1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
|
/*
* The Python Imaging Library
* $Id$
*
* apply convolution kernel to image
*
* history:
* 1995-11-26 fl Created, supports 3x3 kernels
* 1995-11-27 fl Added 5x5 kernels, copy border
* 1999-07-26 fl Eliminated a few compiler warnings
* 2002-06-09 fl Moved kernel definitions to Python
* 2002-06-11 fl Support floating point kernels
* 2003-09-15 fl Added ImagingExpand helper
*
* Copyright (c) Secret Labs AB 1997-2002. All rights reserved.
* Copyright (c) Fredrik Lundh 1995.
*
* See the README file for information on usage and redistribution.
*/
/*
* FIXME: Support RGB and RGBA/CMYK modes as well
* FIXME: Expand image border (current version leaves border as is)
* FIXME: Implement image processing gradient filters
*/
#include "Imaging.h"
Imaging
ImagingExpand(Imaging imIn, int xmargin, int ymargin, int mode)
{
Imaging imOut;
int x, y;
if (xmargin < 0 && ymargin < 0)
return (Imaging) ImagingError_ValueError("bad kernel size");
imOut = ImagingNew(
imIn->mode, imIn->xsize+2*xmargin, imIn->ysize+2*ymargin
);
if (!imOut)
return NULL;
#define EXPAND_LINE(type, image, yin, yout) {\
for (x = 0; x < xmargin; x++)\
imOut->image[yout][x] = imIn->image[yin][0];\
for (x = 0; x < imIn->xsize; x++)\
imOut->image[yout][x+xmargin] = imIn->image[yin][x];\
for (x = 0; x < xmargin; x++)\
imOut->image[yout][xmargin+imIn->xsize+x] =\
imIn->image[yin][imIn->xsize-1];\
}
#define EXPAND(type, image) {\
for (y = 0; y < ymargin; y++)\
EXPAND_LINE(type, image, 0, y);\
for (y = 0; y < imIn->ysize; y++)\
EXPAND_LINE(type, image, y, y+ymargin);\
for (y = 0; y < ymargin; y++)\
EXPAND_LINE(type, image, imIn->ysize-1, ymargin+imIn->ysize+y);\
}
if (imIn->image8) {
EXPAND(UINT8, image8);
} else {
EXPAND(INT32, image32);
}
ImagingCopyInfo(imOut, imIn);
return imOut;
}
Imaging
ImagingFilter(Imaging im, int xsize, int ysize, const FLOAT32* kernel,
FLOAT32 offset, FLOAT32 divisor)
{
Imaging imOut;
int x, y;
FLOAT32 sum;
if (!im || strcmp(im->mode, "L") != 0)
return (Imaging) ImagingError_ModeError();
if (im->xsize < xsize || im->ysize < ysize)
return ImagingCopy(im);
if ((xsize != 3 && xsize != 5) || xsize != ysize)
return (Imaging) ImagingError_ValueError("bad kernel size");
imOut = ImagingNew(im->mode, im->xsize, im->ysize);
if (!imOut)
return NULL;
/* brute force kernel implementations */
#define KERNEL3x3(image, kernel, d) ( \
(int) image[y+1][x-d] * kernel[0] + \
(int) image[y+1][x] * kernel[1] + \
(int) image[y+1][x+d] * kernel[2] + \
(int) image[y][x-d] * kernel[3] + \
(int) image[y][x] * kernel[4] + \
(int) image[y][x+d] * kernel[5] + \
(int) image[y-1][x-d] * kernel[6] + \
(int) image[y-1][x] * kernel[7] + \
(int) image[y-1][x+d] * kernel[8])
#define KERNEL5x5(image, kernel, d) ( \
(int) image[y+2][x-d-d] * kernel[0] + \
(int) image[y+2][x-d] * kernel[1] + \
(int) image[y+2][x] * kernel[2] + \
(int) image[y+2][x+d] * kernel[3] + \
(int) image[y+2][x+d+d] * kernel[4] + \
(int) image[y+1][x-d-d] * kernel[5] + \
(int) image[y+1][x-d] * kernel[6] + \
(int) image[y+1][x] * kernel[7] + \
(int) image[y+1][x+d] * kernel[8] + \
(int) image[y+1][x+d+d] * kernel[9] + \
(int) image[y][x-d-d] * kernel[10] + \
(int) image[y][x-d] * kernel[11] + \
(int) image[y][x] * kernel[12] + \
(int) image[y][x+d] * kernel[13] + \
(int) image[y][x+d+d] * kernel[14] + \
(int) image[y-1][x-d-d] * kernel[15] + \
(int) image[y-1][x-d] * kernel[16] + \
(int) image[y-1][x] * kernel[17] + \
(int) image[y-1][x+d] * kernel[18] + \
(int) image[y-1][x+d+d] * kernel[19] + \
(int) image[y-2][x-d-d] * kernel[20] + \
(int) image[y-2][x-d] * kernel[21] + \
(int) image[y-2][x] * kernel[22] + \
(int) image[y-2][x+d] * kernel[23] + \
(int) image[y-2][x+d+d] * kernel[24])
if (xsize == 3) {
/* 3x3 kernel. */
for (x = 0; x < im->xsize; x++)
imOut->image[0][x] = im->image8[0][x];
for (y = 1; y < im->ysize-1; y++) {
imOut->image[y][0] = im->image8[y][0];
for (x = 1; x < im->xsize-1; x++) {
sum = KERNEL3x3(im->image8, kernel, 1) / divisor + offset;
if (sum <= 0)
imOut->image8[y][x] = 0;
else if (sum >= 255)
imOut->image8[y][x] = 255;
else
imOut->image8[y][x] = (UINT8) sum;
}
imOut->image8[y][x] = im->image8[y][x];
}
for (x = 0; x < im->xsize; x++)
imOut->image8[y][x] = im->image8[y][x];
} else {
/* 5x5 kernel. */
for (y = 0; y < 2; y++)
for (x = 0; x < im->xsize; x++)
imOut->image8[y][x] = im->image8[y][x];
for (; y < im->ysize-2; y++) {
for (x = 0; x < 2; x++)
imOut->image8[y][x] = im->image8[y][x];
for (; x < im->xsize-2; x++) {
sum = KERNEL5x5(im->image8, kernel, 1) / divisor + offset;
if (sum <= 0)
imOut->image8[y][x] = 0;
else if (sum >= 255)
imOut->image8[y][x] = 255;
else
imOut->image8[y][x] = (UINT8) sum;
}
for (; x < im->xsize; x++)
imOut->image8[y][x] = im->image8[y][x];
}
for (; y < im->ysize; y++)
for (x = 0; x < im->xsize; x++)
imOut->image8[y][x] = im->image8[y][x];
}
return imOut;
}
|
